CN111929725B - Seismic data interpolation method, device and equipment - Google Patents
Seismic data interpolation method, device and equipment Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/32—Transforming one recording into another or one representation into another
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- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/61—Analysis by combining or comparing a seismic data set with other data
- G01V2210/616—Data from specific type of measurement
- G01V2210/6161—Seismic or acoustic, e.g. land or sea measurements
Abstract
The embodiment of the specification provides a seismic data interpolation method, a seismic data interpolation device and seismic data interpolation equipment. The method comprises the following steps: setting a regular grid based on the initial seismic data; the initial seismic data having different seismic trace distribution densities in different regions; the regular grid comprises at least one regular grid point; obtaining constructed seismic data in the initial seismic data; the constructed seismic data includes constructed seismic data points corresponding to the regular grid points; using the constructed seismic data points to find a structure tensor for initial seismic data corresponding to the regular grid points; determining local dip angles of initial seismic data corresponding to the regular grid points through the structure tensor; and carrying out interpolation on the initial seismic data according to the local dip angle to obtain interpolated seismic data. According to the method, the corresponding interpolation seismic data are obtained by utilizing the local dip angle according to the seismic data corresponding to the regular grid point, and the interpolation of the seismic data of irregular sampling is realized.
Description
Technical Field
The embodiment of the specification relates to the technical field of seismic signal processing, in particular to a seismic data interpolation method, device and equipment.
Background
In the field of geological exploration, due to the influence of factors such as environment and instruments, the acquired seismic data may have the problems of seismic channel loss, insufficient sampling rate and the like. Under the condition that the seismic data acquired directly do not completely represent geological structures and seismic parameters, the scheme of determining exploration and production by directly utilizing the seismic data may influence the normal operation of exploration and development in practical application. Accordingly, the seismic data may be interpolated to improve the accuracy of the seismic data.
However, in practice, the acquired seismic data may be irregularly sampled seismic data, i.e., seismic data having different trace densities in different areas. When the acquired seismic data are irregularly sampled seismic data, interpolation is directly performed on the irregularly sampled seismic data, so that the interpolated seismic data still have different seismic channel distribution densities, and areas with sparser seismic channel distribution may still have a lower sampling rate, and further utilization of the seismic data in actual production is influenced. Therefore, there is a need for an efficient interpolation method for irregularly sampled seismic data.
Disclosure of Invention
An object of the embodiments of the present specification is to provide a method, an apparatus, and a device for interpolating seismic data, so as to solve a problem of how to interpolate irregularly sampled seismic data to improve a sampling rate thereof.
In order to solve the above technical problem, an embodiment of the present specification provides a seismic data interpolation method, including:
setting a regular grid based on the initial seismic data; the initial seismic data having different seismic trace distribution densities in different regions; the regular grid comprises at least one regular grid point; the regular grid points have a fixed interval therebetween;
obtaining constructed seismic data in the initial seismic data; the constructed seismic data includes constructed seismic data points corresponding to the regular grid points;
using the constructed seismic data points to find a structure tensor for initial seismic data corresponding to the regular grid points; the structure tensor is used for representing the gradient of initial seismic data on the regular grid point;
determining local dip angles of initial seismic data corresponding to the regular grid points through the structure tensor;
and carrying out interpolation on the initial seismic data according to the local dip angle to obtain interpolated seismic data.
An embodiment of the present specification further provides a seismic data interpolation device, including:
a grid setting module for setting a regular grid based on the initial seismic data; the initial seismic data having different seismic trace distribution densities in different regions; the regular grid comprises at least one regular grid point; the regular grid points have a fixed interval therebetween;
a formation seismic data acquisition module for acquiring formation seismic data in the initial seismic data; the constructed seismic data includes constructed seismic data points corresponding to the regular grid points;
a structure tensor calculation module for calculating a structure tensor of the initial seismic data corresponding to the regular grid point by using the constructed seismic data point; the structure tensor is used for representing the gradient of initial seismic data on the regular grid point;
a dip angle determining module for determining local dip angles of initial seismic data corresponding to the regular grid points through the structure tensor;
and the data interpolation module is used for interpolating the initial seismic data according to the local dip angle to obtain interpolated seismic data.
The embodiment of the present specification further provides a seismic data interpolation device, which includes a memory and a processor; the memory to store computer program instructions; the processor to execute the computer program instructions to implement the steps of: setting a regular grid based on the initial seismic data; the initial seismic data having different seismic trace distribution densities in different regions; the regular grid comprises at least one regular grid point; the regular grid points have a fixed interval therebetween; obtaining constructed seismic data in the initial seismic data; the constructed seismic data includes constructed seismic data points corresponding to the regular grid points; using the constructed seismic data points to find a structure tensor for initial seismic data corresponding to the regular grid points; the structure tensor is used for representing the gradient of initial seismic data on the regular grid point; determining local dip angles of initial seismic data corresponding to the regular grid points through the structure tensor; and carrying out interpolation on the initial seismic data according to the local dip angle to obtain interpolated seismic data.
As can be seen from the technical solutions provided by the embodiments of the present specification, in the embodiments of the present specification, a regular grid is constructed, and corresponding structural seismic data is obtained from initial seismic data according to regular grid points in the regular grid, so that a structure tensor corresponding to the regular grid points is obtained by using the structural seismic data, interpolated seismic data corresponding to the regular grid points can be obtained by calculation according to the structure tensor, and interpolation of seismic data obtained by irregular sampling is further achieved. By the method, the interpolation of the seismic data sampled irregularly is realized, the seismic data obtained by measurement are enriched, and the follow-up exploration and production activities are facilitated.
Drawings
In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the specification, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a seismic data interpolation method according to an embodiment of the present disclosure;
FIG. 2 is a schematic illustration of irregularly sampled seismic data in accordance with an embodiment of the present disclosure;
FIG. 3 is a schematic diagram illustrating a local dip angle determined from a structure tensor according to an embodiment of the present disclosure;
FIG. 4 is a schematic illustration of interpolated seismic data according to an embodiment of the present disclosure;
FIG. 5 is a block diagram of a seismic data interpolation apparatus according to an embodiment of the present disclosure;
fig. 6 is a block diagram of a seismic data interpolation device according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present specification without any creative effort shall fall within the protection scope of the present specification.
In order to solve the above technical problem, an embodiment of the present specification provides a seismic data interpolation method. The execution main body of the seismic data interpolation method is computer equipment, and the computer equipment comprises but is not limited to a server, an industrial personal computer, a PC (personal computer) and the like. As shown in fig. 1, the seismic data interpolation method specifically includes the following steps.
S110: setting a regular grid based on the initial seismic data; the initial seismic data having different seismic trace distribution densities in different regions; the regular grid comprises at least one regular grid point; the regular grid points have a fixed spacing therebetween.
The initial seismic data is acquired seismic data. The initial seismic data may include a location to which the measured data corresponds and a specific geological parameter at the location, such as a stratigraphic interface, a geophysical parameter, etc.
In the embodiments of the present specification, the initial seismic data is seismic data obtained under irregular sampling, that is, the initial seismic data has different area distribution densities. As shown in fig. 2, which is a schematic diagram of an initial seismic data. In the schematic diagram, the initial seismic data is seismic data obtained by irregular sampling, and the regional distribution density may be a spatial distribution density, for example, the initial seismic data has different seismic trace distribution densities; the areal distribution density may also be a temporal distribution density, for example with different data acquisition intervals when data is acquired using the data acquisition device. In practical application, the form of the distribution density of the region is not limited, and details are not described here.
The regular grid is a grid set for regularizing the initial seismic data. The regular network may include a horizontal axis and a vertical axis, and the horizontal axis and the vertical axis may be axes respectively corresponding to the horizontal direction and the vertical direction, or axes perpendicular to each other and determined by an operator, which is not described herein again. Since the horizontal axis and the vertical axis in the regular grid have an intersection, the intersection can be determined as the corresponding regular grid point.
The regular grid comprises at least one regular grid point, and the regular grid points can have fixed intervals, so that the seismic data determined based on the regular grid points are seismic data with smooth change, and a corresponding structure tensor can be obtained according to the seismic data corresponding to the regular grid points, and interpolation of the seismic data is realized.
S120: obtaining constructed seismic data in the initial seismic data; the constructed seismic data includes constructed seismic data points corresponding to the regular grid points.
After the regular grid is set, the formation seismic data may be acquired based on the regular grid. Due to the strong correlation between the constructed seismic data and the regular grid points, the relevant parameters corresponding to the regular grid points can be obtained according to the constructed seismic data which has certain relation with the regular grid points.
In some embodiments, in determining the constructed seismic data points, the corresponding constructed seismic data points may be selected based on the distance between the initial seismic data point and the regular grid point. For example, a preset data point number K (K >2) is preset, and then initial seismic data points closest to the regular grid points are sequentially selected until the number of the selected initial seismic data points is equal to the preset data point number K.
Of course, the manner of selecting the structural seismic data points in practical application is not limited to the above example, and for example, all initial seismic data points within the preset structural range may be selected as structural seismic data points based on the regular grid points, which is not limited in this respect.
S130: using the constructed seismic data points to find a structure tensor for initial seismic data corresponding to the regular grid points; the structure tensor is used to represent the gradient of the initial seismic data over the regular grid point.
Because the distance between the constructed seismic data point and the regular grid point is close, the constructed seismic data point and the regular grid point have strong correlation, and the data of the regular grid point can be reflected by the data of the constructed seismic data point.
The structure tensor is a matrix derived from the gradient of the function. It summarizes the main directions of the gradient in a given neighborhood of a point, and how coherent these directions are. In particular, in embodiments of the present description, the structure tensor can be used to represent the gradient of the initial seismic data at the regular grid point.
The structure tensor is a positive semi-definite matrix, and the eigenvalue of the structure tensor is greater than or equal to zero, wherein the eigenvector corresponding to the maximum eigenvalue of the structure tensor is the normal direction of the seismic event representing the point. Since the structure tensor and the internal dip of the irregularly sampled seismic data cannot be directly calculated, the structure tensor can be solved by constructing a local plane equation to estimate the approximate gradients of the initial seismic data in three directions at the regular grid point. In some embodiments, after the gradient of the initial seismic data corresponding to the regular grid point is determined using the constructed seismic data points, the gradient is used to calculate a structure tensor of the initial seismic data corresponding to the regular grid point.
In some embodiments, the gradient may be determined using the constructed seismic data point by first acquiring data point coordinates for the constructed seismic data point including a data point horizontal axis coordinate, a data point vertical axis coordinate, and a data point time coordinate. The data point horizontal axis coordinates and the data point vertical axis coordinates are coordinates corresponding to the horizontal axis and the vertical axis of the regular grid, respectively. The horizontal axis may be, for example, a horizontal axis or an axis close to a horizontal axis in a regular network, and the vertical axis may be an axis perpendicular to the horizontal axis. Of course, in practical application, the corresponding horizontal axis and the corresponding vertical axis may be designated according to specific requirements, which is not described in detail herein. The data point time coordinates are coordinates of the constructed seismic data corresponding to a time axis.
After the data point coordinates are obtained, a gradient solving equation can be constructed by using the data point coordinates and the constructed seismic data. In particular, the gradient solving equation may be
In the formula, xKFor data point abscissa, y, of the Kth constructed seismic data point corresponding to the regular grid pointKData point longitudinal axis coordinates, z, for a Kth constructed seismic data point corresponding to the regular grid pointKAnd a is a data point time coordinate of a Kth constructed seismic data point corresponding to the regular grid point, a is a horizontal axis equation coefficient of the gradient solving equation, β is a vertical axis equation coefficient of the gradient solving equation, and γ is a time equation coefficient of the gradient solving equation. (x)1，y1，z1)、(x2，y2，z2)...(xK，yK，zK) Respectively, data point coordinates corresponding to each of the constructed seismic data points.
The matrix form of the gradient solving equation can be expressed as
The equation coefficients α, β, γ in the gradient solving equation can be solved by using the least square method. The specific calculation process is not described herein again.
By solving the coefficients of the equation, the gradient of the initial seismic data corresponding to the regular grid points can be determined. Specifically, a formula can be utilized
Determining the gradient of the transverse axis, wherexFor the horizontal axis gradient, alpha is the equation for the gradientCoefficient of the cross-axis equation, reuse formula
Determining the gradient of the longitudinal axis, whereyCalculating the longitudinal axis equation coefficient of the equation for the longitudinal axis gradient and beta for the gradient, and formulating
Determining the time gradient, wheretIs the time gradient,. DELTA.t is the sampling interval, t1Is the first sampling time, t2Is the second sampling time, t1And t2The interval between is the sampling interval, xrFor the abscissa, y, of the constructed seismic data pointsrFor the vertical axis coordinates of the constructed seismic data points,
the cross-axis equation coefficients corresponding to the first sample time for the constructed seismic data points,
longitudinal axis equation coefficients corresponding to a first sampling time for the constructed seismic data points,
time equation coefficients corresponding to a first sample time for the constructed seismic data points,
the cross-axis equation coefficients corresponding to the second sample time for the constructed seismic data points,
longitudinal axis equation coefficients corresponding to the second sample time for the constructed seismic data points,
time equation coefficients corresponding to a first sampling time are constructed for the constructed seismic data points.
After the gradient of the initial seismic data corresponding to the regular grid point is obtained through calculation, the structure tensor of the initial seismic data corresponding to the regular grid point can be calculated by using the gradient. Specifically, a formula can be utilized
Calculating a structure tensor, where ST is the structure tensor, ΦxIs the gradient of the transverse axis,. phiyIs a gradient of the longitudinal axis,. phitIs a time gradient. In the above formula<·>Representing a smoothing operator. The obtained structure tensor is a positive semi-definite matrix, a plurality of eigenvectors are corresponding to the structure tensor, and the gradient corresponding to the regular grid point can be determined according to the eigenvector with the largest eigenvalue.
S140: determining local dip angles of the initial seismic data corresponding to the regular grid points from the structure tensor.
After the structure tensor is obtained, the local dip angle of the initial seismic data corresponding to the regular grid point can be determined according to the eigenvector with the largest eigenvalue corresponding to the structure tensor.
Specifically, the structure tensor can be decomposed into the structure feature vectors corresponding to the preset tensor direction. The preset tensor directions may be preset directions, for example, three specific directions in a spatial coordinate system, or directions corresponding to the axes of the structural seismic data in the above steps, which is not limited herein.
Next, based on the structural feature vector decomposed in the above step, the formula ST ═ λ may be useduuuT+λvvvT+λwwwTPerforming a specific decomposition on the structure tensor, wherein ST is the structure tensor and lambdauIs the eigenvalue, λ, of the structural eigenvector uvIs the eigenvalue, λ, of the structural eigenvector vwIs the eigenvalue of the structural eigenvector w, u is the structural eigenvector with the largest eigenvalue, v is the structural eigenvector with the second highest eigenvalue, and w is the structural eigenvector with the smallest eigenvalue, i.e., λu≥λv≥λwAnd the structural feature vector u is determined according to the feature value of the feature vector obtained by decomposition.
After obtaining the structural feature vector u with the maximum feature value, decomposing the structural feature vector u into horizontal axis vector values uxThe vector value u of the vertical axisyAnd time axial magnitude ut. Since the structural feature vector u is a three-dimensional vector and can be mapped in three different directions, the structural feature vector u can be mapped to a horizontal axis, a vertical axis and a time axis respectively to obtain the horizontal axis magnitude uxThe vector value u of the vertical axisyAnd time axial magnitude ut。
Finally, the vector value u of the horizontal axis obtained by the calculation can be usedxThe vector value u of the vertical axisyAnd time axial magnitude utThe local tilt angle is calculated. The local tilt angle may include a horizontal axis tilt angle and a vertical axis tilt angle. In particular, it can be represented by the formula
Calculating the inclination of the horizontal axis, in which θxIs a local transverse axis inclination angle, uxIs a horizontal axis vector value, utIs a time axis magnitude and is calculated by the formula
Calculating the inclination of the longitudinal axis, where θyIs a local longitudinal axis inclination, uyIs a vertical axis vector value, utIs a time axis magnitude.
As shown in fig. 3, which is a schematic diagram of local dip angles corresponding to respective regions obtained by the above method, it can be seen that the above method can effectively obtain local dip angles corresponding to irregularly sampled seismic data at respective regular grid points.
S150: and carrying out interpolation on the initial seismic data according to the local dip angle to obtain interpolated seismic data.
After the local dip angles corresponding to the regular grid points are indirectly acquired, because the regular grid points are in a regular arrangement relationship, the initial seismic data can be directly interpolated by using the local dip angles to calculate interpolated seismic data corresponding to the regular grid points.
In some embodiments, equations may be solved using least squares estimation
In the formula (I), the compound is shown in the specification,
for interpolated seismic data, L is the interpolation operator, ε is the scale parameter, R (θ) is the regularization operator corresponding to the local dip, and d is the initial seismic data.
The method is to interpolate the seismic data in the regular grid by utilizing an inverse interpolation method, wherein the inverse difference value is equivalent to an interpolation system
Where d is at the irregular sampling location niAcquired seismic data f (n)i) M is a regular grid point x in the regular gridjSite acquired seismic data f (x)j) In the form of vectors, L is a simple interpolation operator, for example, a B-spline interpolation algorithm, epsilon is a scale parameter, R is a suitable regularization operator, theta is the inclination of the event axis, and R (theta) is the operator corresponding to the inclination of the event axis using plane wave decomposition filtering as the inclination constraint.
In the case of known amounts of in-phase axis tilt, the interpolation system described above can be converted into
I.e. corresponds to the above equation and, correspondingly, the way of determining the interpolated data is to calculate the least squares solution of the above equation. The detailed solving process is not described herein.
As shown in fig. 4, a schematic diagram of seismic data obtained by interpolation using the seismic data interpolation method can be seen, and the interpolated seismic data is in a regular arrangement form, which indicates that the seismic data interpolation method in the embodiment of the present specification can effectively interpolate seismic data to realize seismic data regularization.
According to the introduction of the seismic data interpolation method, it can be seen that the seismic data interpolation method is used for obtaining the structure tensor corresponding to the regular grid points by constructing the regular grid and obtaining the corresponding structural seismic data in the initial seismic data according to the regular grid points in the regular grid, so that the interpolation seismic data corresponding to the regular grid points can be obtained by calculating according to the structure tensor, and the seismic data obtained by irregular sampling is interpolated. By the method, the interpolation of the seismic data sampled irregularly is realized, the seismic data obtained by measurement are enriched, and the follow-up exploration and production activities are facilitated.
Based on the seismic data interpolation method, the specification also provides an embodiment of a seismic data interpolation device. As shown in fig. 5, the seismic data interpolation apparatus specifically includes the following modules.
A grid setting module 510 for setting a regular grid based on the initial seismic data; the initial seismic data having different seismic trace distribution densities in different regions; the regular grid comprises at least one regular grid point; the regular grid points have a fixed spacing therebetween.
A formation seismic data acquisition module 520 for acquiring formation seismic data in the initial seismic data; the constructed seismic data includes constructed seismic data points corresponding to the regular grid points.
A structure tensor derivation module 530 for deriving a structure tensor for the initial seismic data corresponding to the regular grid point using the constructed seismic data points; the structure tensor is used to represent the gradient of the initial seismic data over the regular grid point.
And an inclination determining module 540, configured to determine local inclinations of the initial seismic data corresponding to the regular grid points through the structure tensor.
And a data interpolation module 550, configured to interpolate the initial seismic data according to the local dip angle to obtain interpolated seismic data.
Based on the seismic data interpolation method, the embodiment of the specification further provides seismic data interpolation equipment. As shown in fig. 6, the seismic data interpolation device includes a memory and a processor.
In this embodiment, the memory may be implemented in any suitable manner. For example, the memory may be a read-only memory, a mechanical hard disk, a solid state disk, a U disk, or the like. The memory may be used to store computer program instructions.
In this embodiment, the processor may be implemented in any suitable manner. For example, the processor may take the form of, for example, a microprocessor or processor and a computer-readable medium that stores computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, an embedded microcontroller, and so forth. The processor may execute the computer program instructions to perform the steps of: setting a regular grid based on the initial seismic data; the initial seismic data having different seismic trace distribution densities in different regions; the regular grid comprises at least one regular grid point; the regular grid points have a fixed interval therebetween; obtaining constructed seismic data in the initial seismic data; the constructed seismic data includes constructed seismic data points corresponding to the regular grid points; using the constructed seismic data points to find a structure tensor for initial seismic data corresponding to the regular grid points; the structure tensor is used for representing the gradient of initial seismic data on the regular grid point; determining local dip angles of initial seismic data corresponding to the regular grid points through the structure tensor; and carrying out interpolation on the initial seismic data according to the local dip angle to obtain interpolated seismic data.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
From the above description of the embodiments, it is clear to those skilled in the art that the present specification can be implemented by software plus a necessary general hardware platform. Based on such understanding, the technical solutions of the present specification may be essentially or partially implemented in the form of software products, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and include instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments of the present specification.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The description is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
While the specification has been described with examples, those skilled in the art will appreciate that there are numerous variations and permutations of the specification that do not depart from the spirit of the specification, and it is intended that the appended claims include such variations and modifications that do not depart from the spirit of the specification.
Claims (10)
1. A method of seismic data interpolation, comprising:
setting a regular grid based on the initial seismic data; the initial seismic data having different areal distribution densities; the regular grid comprises at least one regular grid point; the regular grid points have a fixed interval therebetween;
obtaining constructed seismic data in the initial seismic data; the constructed seismic data includes constructed seismic data points corresponding to the regular grid points;
using the constructed seismic data points to find a structure tensor for initial seismic data corresponding to the regular grid points; the structure tensor is used for representing the gradient of initial seismic data on the regular grid point;
determining local dip angles of initial seismic data corresponding to the regular grid points through the structure tensor;
and carrying out interpolation on the initial seismic data according to the local dip angle to obtain interpolated seismic data.
2. The method of claim 1, wherein the initial seismic data comprises at least one initial seismic data point; the acquiring of the constructed seismic data in the initial seismic data comprises:
and selecting a preset number of constructed seismic data points from the initial seismic data points according to the distance between the initial seismic data points and the regular grid points.
3. The method of claim 1, wherein said using said constructed seismic data points to derive a structure tensor for initial seismic data corresponding to said regular grid point comprises:
using the constructed seismic data points to find gradients of initial seismic data corresponding to the regular grid points;
calculating a structure tensor for the initial seismic data corresponding to the regular grid point using the gradients.
4. The method of claim 3, wherein said using said constructed seismic data points to derive gradients of initial seismic data corresponding to said regular grid points comprises:
acquiring data point coordinates of the constructed seismic data points; the data point coordinates comprise data point horizontal axis coordinates, data point vertical axis coordinates and data point time coordinates;
constructing a gradient solving equation according to the data point coordinates and the constructed seismic data;
solving the gradient by using a least square method to obtain an equation coefficient;
determining gradients of the initial seismic data corresponding to the regular grid points from the equation coefficients.
5. The method of claim 4, wherein constructing a gradient solving equation from the data point coordinates and the constructed seismic data comprises:
constructing a gradient solving equation of
In the formula, xKFor data point abscissa, y, of the Kth constructed seismic data point corresponding to the regular grid pointKData point longitudinal axis coordinates, z, for a Kth constructed seismic data point corresponding to the regular grid pointKTo correspond to the regular gridThe data point time coordinate of the Kth constructed seismic data point of the point, alpha is a horizontal axis equation coefficient of the gradient solving equation, beta is a vertical axis equation coefficient of the gradient solving equation, and gamma is a time equation coefficient of the gradient solving equation;
correspondingly, the gradient comprises a horizontal axis gradient, a vertical axis gradient and a time gradient; the determining gradients of the initial seismic data corresponding to the regular grid points by the equation coefficients comprises:
using formulas
Determining the gradient of the transverse axis, wherexThe gradient of the horizontal axis is adopted, and alpha is the equation coefficient of the horizontal axis of the gradient solving equation;
using formulas
Determining the gradient of the longitudinal axis, whereyCalculating the longitudinal axis equation coefficient of the equation by taking the longitudinal axis gradient as beta;
using formulas
Determining the time gradient, wheretIs the time gradient,. DELTA.t is the sampling interval, t1Is the first sampling time, t2Is the second sampling time, t1And t2The interval between is the sampling interval, xrFor the abscissa, y, of the constructed seismic data pointsrFor the vertical axis coordinates of the constructed seismic data points,
the cross-axis equation coefficients corresponding to the first sample time for the constructed seismic data points,
longitudinal axis equation coefficients corresponding to a first sampling time for the constructed seismic data points,
time equation coefficients corresponding to a first sample time for the constructed seismic data points,
the cross-axis equation coefficients corresponding to the second sample time for the constructed seismic data points,
longitudinal axis equation coefficients corresponding to the second sample time for the constructed seismic data points,
time equation coefficients corresponding to a first sampling time are constructed for the constructed seismic data points.
6. The method of claim 3, wherein the gradient comprises a transverse-axis gradient, a longitudinal-axis gradient, and a temporal gradient; the computing initial seismic data using the gradients includes computing a structure tensor for the regular grid points, including:
using formulas
Calculating a structure tensor, where ST is the structure tensor, ΦxIs the gradient of the transverse axis,. phiyIs a gradient of the longitudinal axis,. phitIs a time gradient.
7. The method of claim 1, wherein the local tilt angles include a local transverse axis tilt angle and a local longitudinal axis tilt angle; the determining, from the structure tensor, local dip angles of initial seismic data corresponding to the regular grid points, comprising:
decomposing the structure tensor into structure eigenvectors corresponding to a preset tensor direction;
using the formula ST ═ λuuuT+λvvvT+λwwwTDecomposing the structure tensor, wherein ST is the structure tensor, lambdauIs the eigenvalue, λ, of the structural eigenvector uvIs the eigenvalue, λ, of the structural eigenvector vwThe characteristic value of a structural characteristic vector w, u is the structural characteristic vector with the largest characteristic value, v is the structural characteristic vector with the second highest characteristic value, and w is the structural characteristic vector with the smallest characteristic value;
decomposing the structural feature vector u into horizontal axis vector values uxThe vector value u of the vertical axisyAnd time axial magnitude ut；
By the formula
Calculating the inclination of the horizontal axis, in which θxIs a local transverse axis inclination angle, uxIs a horizontal axis vector value, utIs a time axial magnitude;
by the formula
Calculating the inclination of the longitudinal axis, where θyIs a local longitudinal axis inclination, uyIs a vertical axis vector value, utIs a time axis magnitude.
8. The method of claim 1, wherein said interpolating the initial seismic data based on the local dip angle to obtain interpolated seismic data comprises:
solving equations using least squares estimation
In the formula (I), the compound is shown in the specification,
for interpolated seismic data, L is the interpolation operator, ε is the scale parameter, R (θ) is the regularization operator corresponding to the local dip, and d is the initial seismic data.
9. A seismic data interpolation apparatus, comprising:
a grid setting module for setting a regular grid based on the initial seismic data; the initial seismic data having different seismic trace distribution densities in different regions; the regular grid comprises at least one regular grid point; the regular grid points have a fixed interval therebetween;
a formation seismic data acquisition module for acquiring formation seismic data in the initial seismic data; the constructed seismic data includes constructed seismic data points corresponding to the regular grid points;
a structure tensor calculation module for calculating a structure tensor of the initial seismic data corresponding to the regular grid point by using the constructed seismic data point; the structure tensor is used for representing the gradient of initial seismic data on the regular grid point;
a dip angle determining module for determining local dip angles of initial seismic data corresponding to the regular grid points through the structure tensor;
and the data interpolation module is used for interpolating the initial seismic data according to the local dip angle to obtain interpolated seismic data.
10. A seismic data interpolation device comprising a memory and a processor;
the memory to store computer program instructions;
the processor to execute the computer program instructions to implement the steps of: setting a regular grid based on the initial seismic data; the initial seismic data having different seismic trace distribution densities in different regions; the regular grid comprises at least one regular grid point; the regular grid points have a fixed interval therebetween; obtaining constructed seismic data in the initial seismic data; the constructed seismic data includes constructed seismic data points corresponding to the regular grid points; using the constructed seismic data points to find a structure tensor for initial seismic data corresponding to the regular grid points; the structure tensor is used for representing the gradient of initial seismic data on the regular grid point; determining local dip angles of initial seismic data corresponding to the regular grid points through the structure tensor; and carrying out interpolation on the initial seismic data according to the local dip angle to obtain interpolated seismic data.
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